Programming Examples Needing Polymorphic Recursion

Inferring types for polymorphic recursive function definitions (abbreviated to polymorphic recursion) is a recurring topic on the mailing lists of popular typed programming languages. This is despite the fact that type inference for polymorphic recursion using for all-types has been proved undecidable. This report presents several programming examples involving polymorphic recursion and determines their typability under various type systems, including the Hindley-Milner system, an intersection-type system, and extensions of these two. The goal of this report is to show that many of these examples are typable using a system of intersection types as an alternative form of polymorphism. By accomplishing this, we hope to lay the foundation for future research into a decidable intersection-type inference algorithm. We do not provide a comprehensive survey of type systems appropriate for polymorphic recursion, with or without type annotations inserted in the source language. Rather, we focus on examples for which types may be inferred without type annotations.

Layered Graphical Models for Tracking Partially-Occluded Objects

Partial occlusions are commonplace in a variety of real world computer vision applications: surveillance, intelligent environments, assistive robotics, autonomous navigation, etc. While occlusion handling methods have been proposed, most methods tend to break down when confronted with numerous occluders in a scene. In this paper, a layered image-plane representation for tracking people through substantial occlusions is proposed. An image-plane representation of motion around an object is associated with a pre-computed graphical model, which can be instantiated efficiently during online tracking. A global state and observation space is obtained by linking transitions between layers. A Reversible Jump Markov Chain Monte Carlo approach is used to infer the number of people and track them online. The method outperforms two state-of-the-art methods for tracking over extended occlusions, given videos of a parking lot with numerous vehicles and a laboratory with many desks and workstations.

Dynamic Programming for Optimal Control of Set-Up Scheduling with Neural Network Modifications

This paper demonstrates an optimal control solution to change of machine set-up scheduling based on dynamic programming average cost per stage value iteration as set forth by Cararnanis et. al. [2] for the 2D case. The difficulty with the optimal approach lies in the explosive computational growth of the resulting solution. A method of reducing the computational complexity is developed using ideas from biology and neural networks. A real time controller is described that uses a linear-log representation of state space with neural networks employed to fit cost surfaces.

Hazard and early warning analysis based on domain specific modeling technologies

An aim of proactive risk management strategies is the timely identification of safety related risks. One way to achieve this is by deploying early warning systems. Early warning systems aim to provide useful information on the presence of potential threats to the system, the level of vulnerability of a system, or both of these, in a timely manner. This information can then be used to take proactive safety measures. The United Nation’s has recommended that any early warning system need to have four essential elements, which are the risk knowledge element, a monitoring and warning service, dissemination and communication and a response capability. This research deals with the risk knowledge element of an early warning system. The risk knowledge element of an early warning system contains models of possible accident scenarios. These accident scenarios are created by using hazard analysis techniques, which are categorised as traditional and contemporary. The assumption in traditional hazard analysis techniques is that accidents are occurred due to a sequence of events, whereas, the assumption of contemporary hazard analysis techniques is that safety is an emergent property of complex systems. The problem is that there is no availability of a software editor which can be used by analysts to create models of accident scenarios based on contemporary hazard analysis techniques and generate computer code that represent the models at the same time. This research aims to enhance the process of generating computer code based on graphical models that associate early warning signs and causal factors to a hazard, based on contemporary hazard analyses techniques. For this purpose, the thesis investigates the use of Domain Specific Modeling (DSM) technologies. The contributions of this thesis is the design and development of a set of three graphical Domain Specific Modeling languages (DSML)s, that when combined together, provide all of the necessary constructs that will enable safety experts and practitioners to conduct hazard and early warning analysis based on a contemporary hazard analysis approach. The languages represent those elements and relations necessary to define accident scenarios and their associated early warning signs. The three DSMLs were incorporated in to a prototype software editor that enables safety scientists and practitioners to create and edit hazard and early warning analysis models in a usable manner and as a result to generate executable code automatically. This research proves that the DSM technologies can be used to develop a set of three DSMLs which can allow user to conduct hazard and early warning analysis in more usable manner. Furthermore, the three DSMLs and their dedicated editor, which are presented in this thesis, may provide a significant enhancement to the process of creating the risk knowledge element of computer based early warning systems.

Exploring processes of indeterminate determinism in music composition, programming and improvisation

This portfolio consists of 15 original musical works. Taking the form of electronic and acousmatic music, multimedia, and scores, these chamber works serve as a result of experimentation and improvisation with individually built computer interfaces. The accompanying commentary provides discourse on the conceptual practice of these interfaces becoming a compositional entity that present a multi-interpretative opportunity to explore, engage, and personalise. Following this, the commentary examines the path of creative decisions and musical choices that formed both these interfaces and the resulting musical and visual works. This portfolio is accompanied by interfaces used, transcoded interfacing behavioural information, and documented improvisational findings.

Practical programming for static average-case analysis: the MOQA investigation

This work considers the static calculation of a program’s average-case time. The number of systems that currently tackle this research problem is quite small due to the difficulties inherent in average-case analysis. While each of these systems make a pertinent contribution, and are individually discussed in this work, only one of them forms the basis of this research. That particular system is known as MOQA. The MOQA system consists of the MOQA language and the MOQA static analysis tool. Its technique for statically determining average-case behaviour centres on maintaining strict control over both the data structure type and the labeling distribution. This research develops and evaluates the MOQA language implementation, and adds to the functions already available in this language. Furthermore, the theory that backs MOQA is generalised and the range of data structures for which the MOQA static analysis tool can determine average-case behaviour is increased. Also, some of the MOQA applications and extensions suggested in other works are logically examined here. For example, the accuracy of classifying the MOQA language as reversible is investigated, along with the feasibility of incorporating duplicate labels into the MOQA theory. Finally, the analyses that take place during the course of this research reveal some of the MOQA strengths and weaknesses. This thesis aims to be pragmatic when evaluating the current MOQA theory, the advancements set forth in the following work and the benefits of MOQA when compared to similar systems. Succinctly, this work’s significant expansion of the MOQA theory is accompanied by a realistic assessment of MOQA’s accomplishments and a serious deliberation of the opportunities available to MOQA in the future.

Health Programming for Clergy: An Overview of Protestant Programs in the United States

The health of clergy is important, and clergy may find health programming tailored to them more effective. Little is known about existing clergy health programs. We contacted Protestant denominational headquarters and searched academic databases and the Internet. We identified 56 clergy health programs and categorized them into prevention and personal enrichment; counseling; marriage and family enrichment; peer support; congregational health; congregational effectiveness; denominational enrichment; insurance/strategic pension plans; and referral-based programs. Only 13 of the programs engaged in outcomes evaluation. Using the Socioecological Framework, we found that many programs support individual-level and institutional-level changes, but few programs support congregational-level changes. Outcome evaluation strategies and a central repository for information on clergy health programs are needed. © 2011 Springer Science+Business Media, LLC.

The effect of correctional facility programming on nonviolent beliefs

Gemstone Team Peace in Prisons

Programming stress-induced altruistic death in engineered bacteria.

Programmed death is often associated with a bacterial stress response. This behavior appears paradoxical, as it offers no benefit to the individual. This paradox can be explained if the death is 'altruistic': the killing of some cells can benefit the survivors through release of 'public goods'. However, the conditions where bacterial programmed death becomes advantageous have not been unambiguously demonstrated experimentally. Here, we determined such conditions by engineering tunable, stress-induced altruistic death in the bacterium Escherichia coli. Using a mathematical model, we predicted the existence of an optimal programmed death rate that maximizes population growth under stress. We further predicted that altruistic death could generate the 'Eagle effect', a counter-intuitive phenomenon where bacteria appear to grow better when treated with higher antibiotic concentrations. In support of these modeling insights, we experimentally demonstrated both the optimality in programmed death rate and the Eagle effect using our engineered system. Our findings fill a critical conceptual gap in the analysis of the evolution of bacterial programmed death, and have implications for a design of antibiotic treatment.

Metabolic programming and PDHK1 control CD4+ T cell subsets and inflammation.

Activation of CD4+ T cells results in rapid proliferation and differentiation into effector and regulatory subsets. CD4+ effector T cell (Teff) (Th1 and Th17) and Treg subsets are metabolically distinct, yet the specific metabolic differences that modify T cell populations are uncertain. Here, we evaluated CD4+ T cell populations in murine models and determined that inflammatory Teffs maintain high expression of glycolytic genes and rely on high glycolytic rates, while Tregs are oxidative and require mitochondrial electron transport to proliferate, differentiate, and survive. Metabolic profiling revealed that pyruvate dehydrogenase (PDH) is a key bifurcation point between T cell glycolytic and oxidative metabolism. PDH function is inhibited by PDH kinases (PDHKs). PDHK1 was expressed in Th17 cells, but not Th1 cells, and at low levels in Tregs, and inhibition or knockdown of PDHK1 selectively suppressed Th17 cells and increased Tregs. This alteration in the CD4+ T cell populations was mediated in part through ROS, as N-acetyl cysteine (NAC) treatment restored Th17 cell generation. Moreover, inhibition of PDHK1 modulated immunity and protected animals against experimental autoimmune encephalomyelitis, decreasing Th17 cells and increasing Tregs. Together, these data show that CD4+ subsets utilize and require distinct metabolic programs that can be targeted to control specific T cell populations in autoimmune and inflammatory diseases.

SMERED: A Bayesian Approach to Graphical Record Linkage and De-duplication

We propose a novel unsupervised approach for linking records across arbitrarily many files, while simultaneously detecting duplicate records within files. Our key innovation is to represent the pattern of links between records as a {\em bipartite} graph, in which records are directly linked to latent true individuals, and only indirectly linked to other records. This flexible new representation of the linkage structure naturally allows us to estimate the attributes of the unique observable people in the population, calculate $k$-way posterior probabilities of matches across records, and propagate the uncertainty of record linkage into later analyses. Our linkage structure lends itself to an efficient, linear-time, hybrid Markov chain Monte Carlo algorithm, which overcomes many obstacles encountered by previously proposed methods of record linkage, despite the high dimensional parameter space. We assess our results on real and simulated data.

Can Cooling Technology Save Many-Core Parallel Programming from Its Programming Woes?

An abstract of this work will be presented at the Compiler, Architecture and Tools Conference (CATC), Intel Development Center, Haifa, Israel November 23, 2015.

Graphical representation and generalization in sequences problems

In this paper we present different ways used by Secondary students to generalize when they try to solve problems involving sequences. 359 Spanish students solved generalization problems in a written test. These problems were posed through particular terms expressed in different representations. We present examples that illustrate different ways of achieving various types of generalization and how students express generalization. We identify graphical representation of generalization as a useful tool of getting other ways of expressing generalization, and we analyze its connection with other ways of expressing it.